GitHub Organization / Team Scraper — Repos, Members & Activity

Extract all public repositories, team members, aggregate programming language breakdowns, and an automated Organization Activity Score (0–100) for any GitHub organization or team.

Built for corporate due diligence, competitive engineering benchmarking, developer recruitment, and open-source intelligence.

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What this Actor does

Given any GitHub organization handle (e.g. vercel, huggingface, microsoft), this Actor extracts:

• All Public Repositories: Name, star count, primary language, last push timestamp, and repo URLs (sorted by popularity).
• Public Members: Member logins, avatar images, and direct profile URLs.
• Languages Breakdown: Aggregate count of repositories utilizing each programming language across the organization.
• Organization Activity Score: Automated 0–100 vitality rating derived from the average health scores of the organization's top 5 repositories.

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Why use this Actor

• Full Org Footprint in Seconds: Avoid manually clicking through dozens of repository pages to map out a team's engineering stack.
• Computed Vitality: Immediately see if an organization's repos are actively maintained or stagnating through the aggregate activityScore.
• Zero Browser Overhead: Fast, lightweight API queries that return structured results without browser rendering costs.
• Structured Sourcing: Directly discover top engineers contributing publicly to key open-source technologies.

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Features

• Configurable Repo Limits: Extract up to 1,000 repositories per organization.
• Optional Member Scraping: Toggle member discovery on or off to optimize execution speed.
• Clean JSON & Tabular Views: Dataset includes pre-configured Apify tabular views for instant inspection and export (JSON, CSV, Excel).

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Use cases

• M&A & Technical Due Diligence: Assess an acquisition target's technical velocity, commit recency, and primary languages.
• Developer Recruiting: Discover key maintainers and public engineers within target tech companies.
• Competitive Intelligence: Track how competitor engineering teams adopt new languages and open-source projects.
• AI Ecosystem Mapping: Survey AI labs and research orgs to map out their software releases.

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Input

Field	Type	Description	Default	Example
org	String (Required)	GitHub organization username (e.g. huggingface, vercel, facebook).	"huggingface"	"vercel"
includeMembers	Boolean	Fetch public organization member profiles.	true	true
maxRepos	Integer	Maximum number of repositories to include in output (1 to 1000).	50	100

Example input

{
  "org": "huggingface",
  "includeMembers": true,
  "maxRepos": 50
}

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Output

Outputs a single comprehensive organization profile record into your default dataset.

Field Definitions

• org (String): Organization handle.
• name (String): Human-readable display name.
• description (String | null): Bio / description of the organization.
• url (String): Canonical GitHub organization URL.
• blog (String | null): Official website or blog URL.
• location (String | null): Stated headquarters or location.
• totalRepos (Integer): Total public repository count.
• totalMembers (Integer): Total public members retrieved.
• totalStars (Integer): Total stars accumulated across all public repositories.
• languagesBreakdown (Object): Map of language names to count of repositories using them.
• primaryLanguage (String | null): Most frequently used language across the organization.
• activityScore (Integer): Aggregate 0–100 activity score across top repos.
• topRepos (Array): Top repositories with { name, fullName, stars, forks, language, description, url, pushedAt }.
• publicMembers (Array): Array of public members { login, url, avatarUrl }.
• fetchedAt (ISO Date): Extraction timestamp.

Example output

{
  "org": "huggingface",
  "name": "Hugging Face",
  "description": "The AI community building the future.",
  "url": "https://github.com/huggingface",
  "blog": "https://huggingface.co",
  "location": "Paris / NYC",
  "totalRepos": 320,
  "totalMembers": 50,
  "totalStars": 920000,
  "languagesBreakdown": {
    "Python": 210,
    "Rust": 25,
    "TypeScript": 35,
    "C++": 12
  },
  "primaryLanguage": "Python",
  "activityScore": 92,
  "topRepos": [
    {
      "name": "transformers",
      "fullName": "huggingface/transformers",
      "stars": 134000,
      "forks": 25000,
      "language": "Python",
      "description": "State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.",
      "url": "https://github.com/huggingface/transformers",
      "pushedAt": "2026-09-28T04:15:00Z"
    }
  ],
  "publicMembers": [
    {
      "login": "julien-c",
      "url": "https://github.com/julien-c",
      "avatarUrl": "https://avatars.githubusercontent.com/u/10695622?v=4"
    }
  ],
  "fetchedAt": "2026-09-28T04:20:59.744Z"
}

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Pricing (Pay-Per-Event)

Event Name	Price (USD)	Charged When
actor-start	$0.01	Charged once when run initializes
org-profile	$0.00035	Charged per organization profile successfully returned

Example cost: Profiling an entire GitHub organization with up to 100 repositories costs $0.01 + $0.00035 = ~$0.0104 total.

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API usage

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_API_TOKEN")

run = client.actor("lovely_radiologist/github-org-scraper").call(run_input={
    "org": "vercel",
    "maxRepos": 50
})

dataset_items = client.dataset(run["defaultDatasetId"]).list_items().items
for org in dataset_items:
    print(f"{org['name']} — {org['totalStars']} stars across {org['totalRepos']} repos (Score: {org['activityScore']}/100)")

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_API_TOKEN' });

const run = await client.actor('lovely_radiologist/github-org-scraper').call({
    org: 'vercel',
    maxRepos: 50
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items[0]);

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Limitations

• Public Members Only: GitHub only exposes members who have explicitly set their organization membership visibility to "Public".
• Rate Limits: Very large orgs (hundreds of repos) query multiple paginated pages. The Actor includes automated backoff to respect GitHub rate limits.

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FAQ

Can I scrape user profiles instead of organizations?

This Actor is optimized for GitHub Organizations and Teams. For individual repositories, use GitHub Repository Insights.

How is the Activity Score derived?

The Actor evaluates the top 5 repos by stargazers within the organization, scoring their commit recency, open issue ratios, and active maintainers, and averages them into a 0–100 scale.

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Support & Related Actors

• GitHub Repository Insights — Deep-dive individual repositories within the organization.
• GitHub Issues & PR Monitor — Monitor issues and pull requests across organization repos.
• GitHub Trending Radar — Find rising organizations and repositories.